The amounts of digital information included in video data are massive and tend to increase along with advances in performance of video cameras. Processing of the video data places large demands on power and computational resources of video-enabled devices and, in particular, wireless communication devices such as cellular phones, personal digital assistants (PDAs), laptop computers, and the like.
Although video compression primarily reduces spatial and temporal redundancy, there are several pre-processing and post-processing operations that are required after the source video has been captured (or extracted from storage as the case may be) and before the reconstructed video is rendered (consumed) at the display. Video Processing places large demands on memory (stored and data transfer) and computational load primarily due to the required arithmetic operations which are directly proportional to power requirements (battery, talk time, etc).
Given the amount of redundancy in video, a proportional reduction in the quantity of such operations should be expected. Since compression ratios are many orders of magnitude (100:1 to 1000:1), a significant reduction in the amount of video data to be processed can be achieved in spite of implementation overheads. Spatio-temporal redundancy can be identified using compression metadata and correspond to a reduction in redundant operations, which saves power. Different levels of redundancy translate to different levels of consumed power and computational loading on a processor.
There is therefore a need for techniques for power and computational load management in video processing and decoding.